Poster Presentation Australian & New Zealand Obesity Society 2014 Annual Scientific Meeting

Obesity and metabolic health risks: An exploration of body mass index and waist circumference combinations (#240)

Stephanie Tanamas 1 , Viandini Permatahati 1 , Winda Ng 1 , Kathryn Backholer 1 , Jonathan Shaw 1 , Anna Peeters 1
  1. Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia

Aim: Recent evidence suggests that a substantial subgroup of the population who have a high-risk waist circumference (WC) do not have an obese body mass index (BMI). Little is known about their health risks. This study aimed to compare the metabolic health risks across different combinations of BMI and WC categories.

 Methods: In 2000, the Australian Diabetes, Obesity and Lifestyle study recruited 11,247 participants aged >=25 years from across Australia. 10,659 participants with complete data were included in our analysis. Height, weight and WC were measured. Adiposity categories were defined according to BMI/WC as: non-obese/ non-obese (N/N), non-obese /obese (N/Ob), obese /non-obese (Ob/N), and obese /obese (Ob/Ob). Logistic regression was used to examine adiposity categories in relation to hypertension, diabetes, dyslipidaemia and cardiovascular disease (CVD).

 Results: The mean age was 48 years, and 50% were men. The proportions of N/N, N/Ob, Ob/N and Ob/Ob were 68%, 12%, 2% and 18%, respectively. The odds for hypertension, dyslipidaemia, and diabetes were increased for those with N/Ob (1.8 (1.4, 2.2); 1.8 (1.4, 2.3); 2.6 (2.1, 3.3), respectively) and Ob/Ob (3.8 (3.3, 4.3); 4.9 (4.0, 6.1); 4.1 (3.4, 5.0), respectively) compared to those with N/N. The odds for CVD were also increased in those with N/Ob (2.7 (2.1, 3.6)) and those Ob/Ob (1.9 (1.3, 2.8)), compared to those with N/N. When stratified by sex and by age, the magnitude of the odds ratios were generally higher in women and in those aged <55 years compared to men and those aged ≥55 years.

Conclusion:  Current population monitoring, which only uses BMI to assess obesity, misses a proportion of the population who are at increased risk for hypertension, diabetes, dyslipidaemia and CVD through excess adiposity. Improved identification of those at increased health risk is paramount for better prioritisation of policy and resources.